论文标题

分散多能系统的面向利益相关者的多标准优化模型

A stakeholder-oriented multi-criteria optimization model for decentral multi-energy systems

论文作者

Körber, Nils, Röhrig, Maximilian, Ulbig, Andreas

论文摘要

市政和地区能源系统的脱碳需要各种技术选择的经济和生态有效转型策略。尤其是在考虑到能源域(例如热和电力供应),所谓分散多能系统(DME)等能源领域的多能系统中,具有多种复杂性。这激发了优化问题的使用,这些问题在计算可行性方面达到了局限性,并结合了所需的细节水平。随着对DMES实施的关注,此问题被加重了,因为从传统的系统角度出发,假定以用户为中心的市场集成观点。除技术概念外,还需要考虑市场制度,例如自我消费和更广泛的能量共享。这凸显了对DME优化模型的需求,该模型涵盖了有关详细技术选择和能源调节的微观经济学观点,以了解能源政策的相互技术和社会经济和社会经济和生态学相互作用。在这种情况下,我们为DME提供了面向利益相关者的多标准优化模型,该模型涉及技术方面以及针对现实世界实施的市场和服务覆盖范围。当前的工作弥合了DMES扩展和操作优化的所需的详细信息建模水平与计算可行性之间的差距。模型细节是通过在嵌套的多级分解方法中应用数学方法的混合组合来实现的,包括遗传算法,Benders分解和Lagrange松弛。这还允许在多节点高性能计算机簇上分布式计算。

The decarbonization of municipal and district energy systems requires economic and ecologic efficient transformation strategies in a wide spectrum of technical options. Especially under the consideration of multi-energy systems, which connect energy domains such as heat and electricity supply, expansion and operational planning of so-called decentral multi-energy systems (DMES) holds a multiplicity of complexities. This motivates the use of optimization problems, which reach their limitations with regard to computational feasibility in combination with the required level of detail. With an increased focus on DMES implementation, this problem is aggravated since, moving away from the traditional system perspective, a user-centered, market-integrated perspective is assumed. Besides technical concepts it requires the consideration of market regimes, e.g. self-consumption and the broader energy sharing. This highlights the need for DMES optimization models which cover a microeconomic perspective under consideration of detailed technical options and energy regulation, in order to understand mutual technical and socio-economic and -ecologic interactions of energy policies. In this context we present a stakeholder-oriented multi-criteria optimization model for DMES, which addresses technical aspects, as well as market and services coverage towards a real-world implementation. The current work bridges a gap between the required modelling level of detail and computational feasibility of DMES expansion and operation optimization. Model detail is achieved by the application of a hybrid combination of mathematical methods in a nested multi-level decomposition approach, including a Genetic Algorithm, Benders Decomposition and Lagrange Relaxation. This also allows for distributed computation on multi-node high performance computer clusters.

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